A globally convergent version of a general recursive algorithm for nonlinear programming

DOI10.1080/02331938608843116zbMath0604.90118OpenAlexW1972427530MaRDI QIDQ3741433

Wolfgang Schneiderheinze

Publication date: 1986

Published in: Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331938608843116

zbMATH Keywords

global convergencereduction methodconstrained nonlinear optimizationsuperlinear rate of convergence

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Newton-type methods (49M15) Numerical methods based on nonlinear programming (49M37)

Cites Work

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• The nonlinear programming method of Wilson, Han, and Powell with an augmented Lagrangian type line search function. I. Convergence analysis
• On the global and superlinear convergence of a discretized version of Wilson's method
• On the convergence of a sequential quadratic programming method with an augmented lagrangian line search function
• Extension of unconstrained minimization methods to linearly constrained problems
• The watchdog technique for forcing convergence in algorithms for constrained optimization
• Perturbed Kuhn-Tucker points and rates of convergence for a class of nonlinear-programming algorithms
• Superlinearly convergent variable metric algorithms for general nonlinear programming problems
• Algorithms for nonlinear constraints that use lagrangian functions

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